AEO Audit Methodology

SkillSearch

Answer Engine Optimization (AEO) audit methodology for LLM visibility. Use when auditing brands for ChatGPT/Gemini mentions, checking LLM citations, analyzing AI search visibility, or when user mentions "AEO", "LLM visibility", "ChatGPT mentions", "Gemini citations", or "AI search optimization".

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the AEO Audit Methodology skill

What this skill tells your AI

The instructions your AI receives, as published by diegosouzapw/awesome-omni-skill in skills/ai-agents/aeo-audit/SKILL.md and read by ahel’s review.

This skill provides the complete Answer Engine Optimization protocol for auditing and optimizing brand visibility in LLM-powered search (ChatGPT, Gemini, Perplexity, etc.).

CRITICAL: Read Protocol First

BEFORE running ANY audit, you MUST read the AEO Protocol SOP:

Read aeo-protocol-sop.md (key sections):
- Lines 1-200: Core methodology
- Lines 850-900: First 50 Words Audit (CRITICAL)
- Lines 1200-1300: Content gap analysis
- Lines 2800-2900: Audit checklist
- Lines 3400-3500: Final checklist

Do NOT skip this step. The protocol is the source of truth.

Core Concepts

What is AEO?

Answer Engine Optimization ensures brands appear in LLM-generated answers, not just traditional search results. LLMs cite sources differently than Google - they need:

  • Facts repeated across 3+ authoritative sources (triangulation)
  • Structured, extractable content
  • Clear entity establishment
  • Technical accessibility (SSR, proper robots.txt)

The Three Search Backends

EngineBackendHow It Works
ChatGPTBing + Memory3-layer cache (parametric → memory → live search)
GeminiGoogle GroundingReal-time Google Search verification
Google AI OverviewGoogle SERPAggregates top organic results

Audit Process

Step 1: Run Brand Audit

Use run_brand_audit MCP tool with:

  • Brand name
  • Product category (be specific: "hair transplant clinic" not "medical")
  • Primary competitor (optional)

Step 2: Discovery Query Testing

Test queries people use BEFORE knowing the brand:

  • "Best [category] in [location]"
  • "Best [category] for [use case]"
  • "Top [category] [year]"
  • "[problem] solution"

Step 2.5: CRITICAL - Run Key Queries 10 Times Each

LLM responses are non-deterministic. Single tests are unreliable.

For top 2-3 discovery queries, run each 10 times per LLM and calculate consistency:

ScoreInterpretation
9-10/10Strong (locked in)
7-8/10Good (consistent)
5-6/10Weak (inconsistent)
1-4/10Poor (rarely mentioned)
0/10Invisible (critical)

A brand at 60% consistency is NOT reliably visible.

Step 2.6: Custom Client Queries

Beyond standard queries, test client-specific "dream queries":

Query TypeExample
Outcome-focused"[category] if money doesn't matter"
Problem-aware"fix bad [category]"
Fear-based"safest [category]"
Lifestyle"[category] for executives"
Attribute-specific"[category] no scars"

Ask during intake: "What 3-5 queries do you WANT to own?"

For 0% visibility queries → create dedicated landing page.

Step 3: Competitive Analysis

  • Check which competitors appear in LLM responses
  • Identify citation sources (what sites are LLMs pulling from?)
  • Map competitive tier (don't compare premium to budget)

Step 4: Gap Analysis

For each query where brand is missing:

  1. What sources ARE being cited?
  2. Is brand mentioned on those sources?
  3. What facts are LLMs extracting?
  4. What content needs to be created?

Step 5: First 50 Words Audit (CRITICAL)

For every key page:

  1. Fetch page content
  2. Extract first 50 words of visible body text
  3. Check for presence of:
    • WHO: Brand/entity name, credentials
    • WHAT: Core offering/service
    • WHERE: Location
    • PRICE: Pricing tier or specific numbers
  4. Score: Pass (3-4) / Partial (2) / Fail (0-1)
  5. Document specific rewrites needed

Why this matters: LLMs weight early content heavily. Facts not in first 50 words often aren't extracted.

Scoring Framework

MetricWeightMeasurement
ChatGPT Mentions30%Brand appears in X/8 queries
Gemini Mentions30%Brand appears in X/8 queries
Google AI Overview20%Brand in AI Overview snippets
Citation Quality20%Authoritative sources citing brand

Key Audit Queries (Template)

  1. What is [brand]? - Basic recognition
  2. Best [category] in [location] - Discovery
  3. [Brand] vs [competitor] - Comparison
  4. [Brand] reviews - Reputation
  5. [Brand] pricing - Commercial intent
  6. Best [category] for [use case] - Use-case discovery
  7. [Problem] specialist [location] - Problem-aware discovery
  8. Top [category] [year] - List inclusion

Red Flags in Audits

  • ❌ Brand not mentioned in discovery queries (acquisition problem)
  • ❌ Competitor mentioned but brand isn't (content gap)
  • ❌ Incorrect facts in LLM responses (reputation risk)
  • ❌ No citations to brand's own website (authority problem)
  • ❌ Only mentioned with competitor comparisons (positioning issue)

Quick Reference

For detailed methodology, see:

Signals

GitHub stars
57
Forks
19
Last commit
Mar 2026
Advanced
Catalog kind
skill
Gateway key
aeo-audit
Source
github.com/diegosouzapw/awesome-omni-skill